Television and video technology has long relied on trickery to fool the human eye into believing that the television or video signal accurately reflects the events occurring. For instance, conventional video technology such as the NTSC (National Television Standards Committee) standard uses “interlaced video,” in which a single image or frame comprises two fields that are taken {fraction (1/60)} second apart. Each frame contains 525 scan lines divided into two fields. The first, or odd, field comprises the odd numbered lines (e.g., 1, 3, . . . 525) while the second, even field forms the even numbered lines (e.g., 2, 4, . . . 524). These two fields, during display of the frame they form, are interlaced so that the odd numbered scan lines are inserted between the even numbered scan lines, much like the interlacing that would occur when one interlaces the fingers of one hand with the fingers of another. Since each frame comprises two interlaced fields (even and odd) each captured {fraction (1/60)} second apart, the frames themselves are captured at a rate of 30 frames per second.
In most video applications, the very short delay ({fraction (1/60)} second) between capture of fields means that even if the subject moves during filming, any artifacts of motion will be virtually undetectable. (An example of motion artifacts can be seen in old silent movies, which operated at fairly low frame speeds.) The high rate at which the recorder captures frames and the slight time separation between the fields within each frame results in minimal blurring in the video. Even when the subject being video-recorded is in motion, for example, a moving car or a runner, such motion artifact will be substantially undetectable to the human eye in the captured frame. Additional, in many applications, humans tend to ignore even detectable motion artifacts in video because a particular motion artifact (for example, blurring because of subject movement) is often quickly replaced with another frame or series of frames missing that artifact. Thus, in some applications, the speed of frame capture and the continual refreshment of interlaced fields is sufficient to avoid noticeable blurring of video images.
However, in many applications, the rate at which fields are scanned and frames are captured is not sufficiently high to prevent motion artifacts from causing image distortion problems in the displayed video. Applications in which image distortion problems may be caused by motion artifacts include, for example, video and images taken from endoscopic or other surgery, sports still frames, or other video in which the camera and subject are moving independently. U.S. Pat. No. 5,191,413 to Edgar gives a practical example of this. Edgar states that “if a subject were to move a hand during the capturing process, sequential fields will be generated which will capture the hand in two distinctly different positions. However, operation of typical interlace systems call for the two fields to be continuously refreshed alternately on the display screen. The results of this may be the appearance of the hands engaging in a jittery or shaking motion at the frequency of 30 times a second giving rise to highly undesirable images.” This phenomenon is also illustrated in U.S. Pat. No. 5,329,317 to Naimpally, et al.
These motion artifacts are particularly pronounced when the video in question has been magnified. For example, videos are often taken and magnified in endoscopic or laparoscopic surgery. Video images are taken by a high resolution camera coupled to an endoscope optic or laparoscope optic. Such images are magnified tremendously by the scope optic and, as a result, the captured images are extremely sensitive to motion. Thus, a small movement in an image field results in a much larger change in the viewed field, and such magnified motion appears to be more global than local. In addition, because of this magnification, such motion is exaggerated by the time separation between the two field components of the captured frame.
Motion effects in captured frames are created in at least two different ways, each of the at least two ways resulting in different types of motion artifact. One type of motion effect is generated by movement of the endoscope camera by the surgeon. Endoscope movement can result in a “uniform motion-related error” between the odd and even fields. This type of motion effect is known generally as “linear artifact.” As both fields are captured, endoscope movement causes a nearly identical image to be shifted in direct proportion to the velocity of endoscope movement, thus producing linear artifact. A second type of motion effect is created by movement within the image field of the camera. Such motion may be due to movement of surgical tools by the surgeon or by movement of the patient, such as with breathing. This type of motion effect is localized to the region of the image in which movement of the surgical tools or the patient tissue is being viewed, and is known as “regional artifact.” The substantial magnification by the endoscope or laparoscope optic exacerbates the distorting effect of motion in a captured image caused by both linear artifacts and regional artifacts.
In sensitive applications, such as surgery, it is important to provide the most stable and artifact-free image possible. Efforts have been made in the past to correct for these motion artifacts. For example, video printers available from manufacturers such as Sony have “motion check” firmware. That firmware looks for motion artifacts developed within a particular image and alerts the user when it finds them. The user can then correct for the motion artifact. The correction usually involves dropping one of the two fields forming the image, which greatly reduces the vertical resolution of the video being displayed or printed. Another conventional technique for correcting for motion is to drop one of the two fields and replace the discarded field by repeating the remaining field. This results in an image that exaggerates only half the captured information, resulting in lower resolution. Also, some commercial software applications have motion correction features that can be performed by the user, although the features are often difficult to implement by those not technically versed in its use. Adobe has such software.
Another approach to correcting for motion artifacts has been to compare the difference between pixels in two adjacent fields to a fixed threshold value. If the threshold is exceeded, then the value in one pixel is replaced. The replacement value may be determined by averaging the value of pixels in adjacent lines. If, however, the difference between pixels does not exceed the fixed threshold, no action is taken to change a pixel value. This process is repeated for each pixel in each line of each frame. An example of this approach as applied to motion artifacts within an endoscopic image field is described in U.S. Pat. No. 5,877,819 to Branson.
Conventional methods for correcting for motion artifacts in highly magnified videos do not result in the highest quality picture. Moreover, they often require users with specialized skills, and lack flexibility. Thus, there is a need for a method and system for correcting for motion artifacts in highly magnified videos that yields a high resolution image. There is also a need for such a method and system that is dynamic with respect to pixel value thresholds so as to increase flexibility in further pixel value analysis and replacement. Moreover, there is a particular need for such methods and systems in sensitive applications, such as surgery.